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Neth Heart J. 2019 Sep;27(9):403-413. doi: 10.1007/s12471-019-01311-1.

Artificial intelligence in cardiovascular imaging: state of the art and implications for the imaging cardiologist.

Author information

1
Department of Cardiology, location VUmc, Amsterdam University Medical Centres, Amsterdam, The Netherlands.
2
Department of Experimental Cardiology, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands.
3
Department of Radiology, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands.
4
Department of Cardiovascular Medicine, Flinders Medical Centre, Bedford Park, SA, Australia.
5
South Australian Health and Medical Research Institute, Adelaide, SA, Australia.
6
Cardiologie Centra Nederland, Amsterdam, The Netherlands.
7
South Australian Health and Medical Research Institute, Adelaide, SA, Australia. Johan.Verjans@SAHMRI.com.
8
Australian Institute for Machine Learning, University of Adelaide, Adelaide, SA, Australia. Johan.Verjans@SAHMRI.com.
9
Dept of Cardiology, Royal Adelaide Hospital, Adelaide, SA, Australia. Johan.Verjans@SAHMRI.com.

Abstract

Healthcare, conceivably more than any other area of human endeavour, has the greatest potential to be affected by artificial intelligence (AI). This potential has been shown by several reports that demonstrate equal or superhuman performance in medical tasks that aim to improve efficiency, diagnosis and prognosis. This review focuses on the state of the art of AI applications in cardiovascular imaging. It provides an overview of the current applications and studies performed, including the potential value, implications, limitations and future directions of AI in cardiovascular imaging.It is envisioned that AI will dramatically change the way doctors practise medicine. In the short term, it will assist physicians with easy tasks, such as automating measurements, making predictions based on big data, and putting clinical findings into an evidence-based context. In the long term, AI will not only assist doctors, it has the potential to significantly improve access to health and well-being data for patients and their caretakers. This empowers patients. From a physician's perspective, reliable AI assistance will be available to support clinical decision-making. Although cardiovascular studies implementing AI are increasing in number, the applications have only just started to penetrate contemporary clinical care.

KEYWORDS:

Artificial intelligence; Cardiac imaging techniques; Clinical decision-making; Machine learning; Medical imaging

PMID:
31399886
PMCID:
PMC6712136
DOI:
10.1007/s12471-019-01311-1

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